By some estimates, up to half of all mechanical failures in process plants are induced by process conditions. Therefore, providing feedback to an operator that the process machines are being operated in a non-optimal configuration provides a way for the operator to avoid harmful operating states, thereby substantially extending mean time between failures (MTBF) or mean time between repairs (MTBR) on production assets.
Vibration analysis is a well proven technology for detecting faults in rotating machinery. The process of determining the severity and specifics of a fault can be very involved. Part of the analysis process involves determining whether periodic signals are present. While maintenance personnel are concerned with detailed analyses of faults, operations personnel only want to know if a problem exists. Providing a few fault-related parameters to the operator can be sufficient in accomplishing this task. Fault-related parameters can be related to amplitudes of energy from particular vibration frequencies (bandwidth), signal processing techniques such as PeakVue™, and the presence of periodic signals. Parameters calculated from bandwidth and signal processing techniques are well defined. However, a parameter indicating the presence of periodic signals has not been defined.
Further, the ability to detect mechanical faults in industrial machinery is a task requiring skilled analytical personnel with years of training and experience. Because of budgetary and personnel constraints, a qualified analyst may be pressed to analyze most or all of the equipment in a plant. Any technology, technique or tool that can simplify the analyst's job is valuable. Although the Fast Fourier Transform (FFT) is a technique that may be used to simplify the analyst's job, identifying important peaks in an FFT plot can be difficult due to low amplitude and noise issues. The analysis could be made easier with the derivation of a graph that reflects only periodic signals present in the measurement.
What is needed, therefore, is a system for calculating a periodic signal parameter based on an autocorrelation waveform derived form a vibration waveform. Those skilled in the art will see that autocorrelation is one of several ways to quantify the periodicity in a given signal. What is also needed is a system for deriving a graph, also referred to herein as a “periodic information plot,” that reflects only periodic signals present in a measurement waveform.